AIMC Topic: Deep Learning

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A model-based constrained deep learning clustering approach for spatially resolved single-cell data.

Genome research
Spatially resolved scRNA-seq (sp-scRNA-seq) technologies provide the potential to comprehensively profile gene expression patterns in tissue context. However, the development of computational methods lags behind the advances in these technologies, wh...

Class-Imbalanced Deep Learning via a Class-Balanced Ensemble.

IEEE transactions on neural networks and learning systems
Class imbalance is a prevalent phenomenon in various real-world applications and it presents significant challenges to model learning, including deep learning. In this work, we embed ensemble learning into the deep convolutional neural networks (CNNs...

Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method.

Computational intelligence and neuroscience
In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learni...

Analysis of the Correlation between College Music Education and Public Mental Health Based on Deep Learning.

Journal of environmental and public health
With the continuous changes of college music education and public mental health problems, conventional solutions are no longer sufficient. At this time, we adopted a method based on deep learning to study them. The experiments showed that ① deep lear...

Higher Education Environment Monitoring and Quality Assessment Model Using Big Data Analysis and Deep Learning.

Journal of environmental and public health
A university exists to help students develop their skills. The goal of university development is to raise the standard of personnel training, and the core component of university development is teaching quality. Whether the level of practical trainin...

A Classification Method for Thoracolumbar Vertebral Fractures due to Basketball Sports Injury Based on Deep Learning.

Computational and mathematical methods in medicine
OBJECTIVE: There are more and more basketball competitions, to propose a classification method of thoracolumbar fractures to assist in the diagnosis of basketball injuries, to analyze the feasibility of its clinical application, and to improve the re...

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model.

Journal of environmental sciences (China)
Recently, the global background concentration of ozone (O) has demonstrated a rising trend. Among various methods, groun-based monitoring of O concentrations is highly reliable for research analysis. To obtain information on the spatial characteristi...

Prediction of the proximate analysis parameters of refuse-derived fuel based on deep learning approach.

Environmental science and pollution research international
Determination of proximate characteristics can be achieved using conventional analyses methods that require a certain amount of time. In cement factories, refuse-derived fuel (RDF) is continuously fed to a kiln by a conveyor belt, so even if an inapp...

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the ...